Step 5: Install packages in your Python environment
Previous step: Run code in the debugger
The Python developer community has produced thousands of useful packages that you can incorporate into your own projects. Visual Studio provides a UI to manage packages in your Python environments.
Select the View > Other Windows > Python Environments menu command. The Python Environments window opens as a peer to Solution Explorer and shows the different environments available to you. The list includes both environments that you installed using the Visual Studio installer and those you installed separately. The environment in bold is the default environment that's used for new projects.
The environment's Overview tab provides quick access to an Interactive window for that environment along with the environment's installation folder and interpreters. For example, select Open interactive window and an Interactive window for that specific environment appears in Visual Studio.
Select the Packages tab and you see a list of packages that are currently installed in the environment.
matplotlibby entering its name into the search field, then select the pip install
Consent to elevation if prompted to do so.
After the package is installed, it appears in the Python Environments window. The X to the right of the package uninstalls it.
A small progress bar may appear underneath the environment to indicate that Visual Studio is building its IntelliSense database for the newly-installed package. The IntelliSense tab also shows more detailed information. Note that until that database is complete, IntelliSense features like auto-completion and syntax checking won't be active in the editor for that package.
Note that Visual Studio 2017 version 15.6 and later uses a different and faster method for working with IntelliSense, and displays a message to that effect on the IntelliSense tab.
Create a new project with File > New > Project, selecting the Python Application template. In the code file that appears, paste the following code, which creates a cosine wave like the previous tutorial steps, only this time plotted graphically:
from math import radians import numpy as np # installed with matplotlib import matplotlib.pyplot as plt def main(): x = np.arange(0, radians(1800), radians(12)) plt.plot(x, np.cos(x), 'b') plt.show() main()
Run the program with (F5) or without the debugger (Ctrl+F5) to see the output: